sdf_rbinom: Generate random samples from a binomial distribution

sdf_rbinomR Documentation

Generate random samples from a binomial distribution

Description

Generator method for creating a single-column Spark dataframes comprised of i.i.d. samples from a binomial distribution.

Usage

sdf_rbinom(
  sc,
  n,
  size,
  prob,
  num_partitions = NULL,
  seed = NULL,
  output_col = "x"
)

Arguments

sc

A Spark connection.

n

Sample Size (default: 1000).

size

Number of trials (zero or more).

prob

Probability of success on each trial.

num_partitions

Number of partitions in the resulting Spark dataframe (default: default parallelism of the Spark cluster).

seed

Random seed (default: a random long integer).

output_col

Name of the output column containing sample values (default: "x").

See Also

Other Spark statistical routines: sdf_rbeta(), sdf_rcauchy(), sdf_rchisq(), sdf_rexp(), sdf_rgamma(), sdf_rgeom(), sdf_rhyper(), sdf_rlnorm(), sdf_rnorm(), sdf_rpois(), sdf_rt(), sdf_runif(), sdf_rweibull()


sparklyr documentation built on Aug. 17, 2022, 1:11 a.m.